Interoperability in Healthcare IT: Why It Still Matters and How We Finally Get There

If you’ve worked in healthcare technology for more than five minutes, you’ve heard the word “interoperability” enough times to last a lifetime. It’s been a keynote topic at HIMSS for over a decade. It’s baked into federal legislation. It’s the stated priority of every major EHR vendor’s product roadmap.

And yet, in 2025, an emergency physician in one health system still can’t reliably pull up a patient’s medication list from the hospital across town.

The question isn’t whether interoperability matters — that debate ended years ago. The real question is why progress remains so painfully incremental despite billions of dollars in investment, and what it will actually take to close the gap.

The State of Play: Better, But Not Good Enough

Let’s give credit where it’s due. The healthcare industry has made genuine progress on data exchange. The 21st Century Cures Act and its information blocking provisions have created real consequences for organizations that hoard data. National exchange networks like Carequality and CommonWell have expanded dramatically. FHIR-based APIs are now a regulatory requirement, not a vendor talking point.

But the metrics that matter most tell a more complicated story. According to recent research, approximately 57% of physicians still identify interoperability as their primary barrier to effective care coordination. Clinician satisfaction with the data they receive through exchange networks has barely budged since 2018.

The problem has shifted. It’s no longer that data can’t move between systems — increasingly, it can. The problem is that the data that arrives is often duplicative, poorly mapped, inconsistently formatted, and clinically unusable without significant manual reconciliation.

In other words, we’ve solved the plumbing problem in many places. We haven’t solved the water quality problem.

The Four Barriers That Still Stand in the Way

1. Legacy EHR Silos

Despite the dominance of a few major EHR platforms, the installed base across the healthcare ecosystem remains remarkably fragmented. Small practices, rural hospitals, behavioral health facilities, long-term care facilities, and public health agencies often run on systems that were never designed for modern data exchange. Replacing these systems is prohibitively expensive. Interfacing with them is technically complex and rarely a vendor priority.

2. Vendor Lock-In

The EHR market’s concentration has created a paradox: the largest vendors have the technical capability to enable seamless interoperability, but limited commercial incentive to do so. When switching costs are high and data portability is low, the vendor’s competitive moat deepens. Some vendors have made genuine strides toward openness — Epic’s Care Everywhere network is a notable example — but system-wide, the incentive structure still rewards closed ecosystems.

3. The Trust Deficit

Technology alone doesn’t explain the interoperability gap. A significant and underappreciated barrier is the lack of trust between payers and providers. Data sharing requires a degree of transparency that many organizations find uncomfortable. Providers worry that sharing data with payers will be used to deny claims or reduce reimbursement. Payers worry that incomplete provider data leads to inaccurate risk adjustment. This mutual suspicion creates friction that no API specification can resolve.

4. Regulatory Compliance Fatigue

Roughly 59% of healthcare organizations report challenges meeting evolving information blocking and interoperability regulations. The rules themselves are complex, the enforcement mechanisms are still maturing, and many organizations — particularly smaller ones — lack the dedicated compliance resources to stay current. The result is a landscape where regulatory intent is strong but on-the-ground adoption is uneven.

The Path Forward: Standards, AI, and Governance

Despite these barriers, there are concrete strategies that are producing measurable results.

FHIR as the Foundation

Fast Healthcare Interoperability Resources (FHIR) has moved from “promising standard” to “regulatory requirement,” and its impact is real. FHIR provides a common language for structuring and exchanging clinical data, and its RESTful API architecture makes it significantly more developer-friendly than older standards like HL7 v2 or CDA.

The key now is depth of FHIR implementation. Many organizations have achieved basic FHIR compliance — supporting patient access APIs, for example — but haven’t yet extended FHIR-based exchange to clinical workflows like referral management, prior authorization, or care plan coordination. The organizations seeing the greatest interoperability gains are those treating FHIR not as a compliance checkbox, but as a core integration architecture.

AI for Data Normalization

One of the most promising — and underreported — applications of artificial intelligence in healthcare IT is automated data normalization. When a patient’s allergy list arrives from three different systems using three different coding schemes and three different levels of specificity, AI and machine learning tools can reconcile those records into a single, clinically accurate summary.

This isn’t a theoretical application. Several health systems and HIE networks are already deploying NLP-driven reconciliation tools that automatically map disparate terminology to standardized vocabularies (SNOMED CT, RxNorm, LOINC), flag conflicts, and present clinicians with a cleaned, unified patient record.

TEFCA: A National Governance Layer

The Trusted Exchange Framework and Common Agreement (TEFCA), coordinated by the Office of the National Coordinator for Health IT, aims to provide a nationwide governance and policy layer for health data exchange. Rather than requiring every organization to negotiate individual data-sharing agreements, TEFCA establishes common rules of the road that participating networks agree to follow.

TEFCA is still in its early adoption phase, but its potential to simplify cross-network data exchange — particularly for use cases like public health reporting and payer-provider data sharing — is substantial.

Cloud-Based Integration Platforms

The migration to cloud infrastructure is enabling a new generation of integration platforms that can aggregate, normalize, and route data across organizational boundaries in near-real time. These platforms reduce dependence on costly on-premise interface engines and offer the scalability that legacy infrastructure simply can’t match.

The Human Side of Interoperability

It’s worth noting that interoperability challenges don’t just affect hospitals and health systems. They ripple downstream to every provider who needs to coordinate care across organizational boundaries — including nurse practitioners running independent or semi-independent practices.

For NPs in states that require collaborative physician agreements, the administrative overhead of maintaining compliant documentation, coordinating care plans, and managing shared patient records across different systems is a daily reality. The financial and logistical considerations of these arrangements — including understanding what a collaborating physician actually costs — intersect directly with the interoperability conversation. When systems don’t talk to each other, the burden of reconciliation falls on individual providers, and that burden has real costs in time, money, and cognitive load.

What Organizations Should Do Now

For healthcare IT leaders looking to accelerate interoperability progress in 2025, the playbook is increasingly clear: